SQL Staurday #763
Pre-Con sessions

Learn about Pre-Conn sessions

André Melancia: SQL Optimization

Price: 90 Euro (VAT excl.)

Summary

You bought a server just a few months ago, but suddenly it is running at 98% CPU, 98% RAM and 100% of your patience. Your client is screaming, your boss doesn’t want to buy new hardware, and you don’t know what to do. You probably have a performance problem.

In this workshop, we’ll cover the typical problem scenarios and how to optimize them to make the best of your current hardware.

Although the focus of this workshop is SQL Server, many of the recommendations also apply to MariaDB/MySQL, Oracle, and other DBMS, both on-premises and cloud-based.

Marcin Szeliga: Machine Learning with SQL Server 2016/2017

Price: 90 Euro (VAT excl.)

Summary

SQL Server Machine Learning Services (R Services in 2016) is the result of embedding a predictive analytics and data science engine within SQL Server. The open-source programming languages R and Python have for a long time been popular for advanced analytics. Among many strength, both languages have some weak points: limited scalability, sub-optimal performance, and complex deployment.

Having Machine Learning in SQL Server helps here in several ways. First, you can utilize the same security model that you’re using for any other access to that same data. Second, as the data volumes grow, you aren’t needing to move (and then refresh) the data. You can process it right where it is. Third, you can take advantage of the multi-threaded architecture of SQL Server.

Remember, while being able to train and retrain predictive models is important and is hard work, it’s when you use those models to create predictions that the real value becomes apparent.

This advanced workshop combine practice with theory. By building ML models you will learn:

How to execute in-database R and Python scripts.

How to visualize data.

Why feature engineering is so important and how to do it efficiently.

How the k-means algorithm works and how to perform customer clustering.

What linear regression has in common with artificial neural net and how to use them for predictive maintenance.

Why ensemble models, like Boosted Trees, are so powerful and how to use them for predictions.

About the trainer

Since 2006 invariably awarded Microsoft Most Valuable Professional title, now in AI category. A speaker at numerous conferences across Europe, as well as at user groups meetings, author of many books and articles devoted to Microsoft Data Platform. Professionally university teacher, independent consultant, and architect totally focused on SQL Server and Azure.